Filters








270 Hits in 6.9 sec

Content Download in Vehicular Networks in Presence of Noisy Mobility Prediction

Francesco Malandrino, Claudio Casetti, Carla-Fabiana Chiasserini, Marco Fiore
2014 IEEE Transactions on Mobile Computing  
Analytical and simulation results show that our approach to content downloading through vehicular networks can achieve a 70% offload of the cellular network.  ...  We investigate the effectiveness of vehicular networks in this task, considering that roadside units can exploit mobility prediction to decide which data they should fetch from the Internet and to schedule  ...  Barberis for providing the mobility trace, and Regione Piemonte for supporting this work through the IoT | ToI project (POR F.E.S.R. 2007/2013).  ... 
doi:10.1109/tmc.2013.128 fatcat:ah36wvomkjh67ork2qfmeuk2ta

Predictive methods for improved vehicular WiFi access

Pralhad Deshpande, Anand Kashyap, Chul Sung, Samir R. Das
2009 Proceedings of the 7th international conference on Mobile systems, applications, and services - Mobisys '09  
In our experiments with a vehicular client accessing road-side APs, the handoff strategy improves download performance by roughly a factor of 2 relative to the state-of-the-art.  ...  Experimental performance evaluation reveals that the predictability of mobility and connectivity is high enough to be useful in such protocols.  ...  Excellence in Wireless and Information Technology (CEWIT).  ... 
doi:10.1145/1555816.1555843 dblp:conf/mobisys/DeshpandeKSD09 fatcat:r47qnq4lw5ajdo4ln77i6yoi5q

Content distribution in VANETs

Mario Gerla, Chuchu Wu, Giovanni Pau, Xiaoqing Zhu
2014 Vehicular Communications  
Advances in vehicular communications technology are making content distribution to vehicles more effective and increasingly more popular.  ...  This paper presents state of the art technologies and protocols for content distribution in VANETs.  ...  The key feature in their approach is the use of multi-hop randomized network coding in order to achieve reliable dissemination of contents in the vehicular network.  ... 
doi:10.1016/j.vehcom.2013.11.001 fatcat:int2kgzmfjcd7fjlwbdnhzxfmy

Dealing with Node Mobility in Ad Hoc Wireless Network [chapter]

Mario Gerla, Ling-Jyh Chen, Yeng-Zhong Lee, Biao Zhou, Jiwei Chen, Guang Yang, Shirshanka Das
2005 Lecture Notes in Computer Science  
Link prediction In typical mobile networks, nodes exhibit some degree of regularity in mobility patterns.  ...  in the presence of transient connectivity.  ... 
doi:10.1007/11419822_3 fatcat:m2bwlanaibduxpjpvr5tncbwkm

Wireless Social Networks: A Survey of Recent Advances, Applications and Challenges

Furqan Jameel, Shurjeel Wyne, Dushantha Nalin K. Jayakody, Georges Kaddoum, Richard O'Kennedy
2018 IEEE Access  
In fact, the social networking concepts of centrality and community have been investigated for an efficient realization of novel wireless network architectures.  ...  The potential challenges in communication network design are also highlighted, for a successful implementation of social networking strategies.  ...  ., in [200] , provided a proof-of-concept (PoC) where a selected group of members can download a list of content.  ... 
doi:10.1109/access.2018.2872686 fatcat:xgasj62jprfcbldo5uyhf63niq

Crowd Intelligence for Sustainable Futuristic Intelligent Transportation System: A Review

Rathin Shit
2020 IET Intelligent Transport Systems  
The crowd-intelligence-based mobility, traffic control, traffic prediction, parking solutions have been discussed in this survey.  ...  In this context, a crowd intelligence system plays a key role in interactive system development.  ...  for crowdsensing, dynamic topology of vehicular network and user mobility modelling.  ... 
doi:10.1049/iet-its.2019.0321 fatcat:2krdzlefdndbxfx3uhlzexhps4

Wireless Edge Computing with Latency and Reliability Guarantees [article]

Mohammed S. Elbamby, Cristina Perfecto, Chen-Feng Liu, Jihong Park, Sumudu Samarakoon, Xianfu Chen, Mehdi Bennis
2019 arXiv   pre-print
While current state-of-the-art networks communicate, compute, and process data in a centralized manner (at the cloud), for latency and compute-centric applications, both radio access and computational  ...  This article will provide a fresh look to the concept of edge computing by first discussing the applications that the network edge must provide, with a special emphasis on the ensuing challenges in enabling  ...  Proactive networks require efficient methods to predict the popularity of the content to be cached, as well as high storage capacity to cache this content.  ... 
arXiv:1905.05316v1 fatcat:bxbacmfeobddxczdpp6x7xcsr4

2013 Annual Index

2014 IEEE Transactions on Mobile Computing  
-that appeared in this periodical during 2013, and items from previous years that were commented upon or corrected in 2013.  ...  The primary entry includes the coauthors' names, the title of the paper or other item, and its location, speci ed by the publication abbreviation, year, month, and inclusive pagination.  ...  A Scalable Server Architecture for Mobile Presence Services in Social Net-Predicting Human Movement Based on Telecom's Handoff in Mobile Net-Networks.  ... 
doi:10.1109/tmc.2014.1 fatcat:auiwkgw5hraghc33kunuaddexq

khan2020.pdf

Khan Zulfiqar
2021 figshare.com  
caching • Data sparsity due to mobility • High back-haul congestion • High latency in content delivery • Deep learning assisted cache content prediction • Reinforcement learning based mobility-aware  ...  have significant importance in vehicular networks.  ... 
doi:10.6084/m9.figshare.14099087.v1 fatcat:nipztbbrgrcwvp2dy6m2gbyytm

Edge-Computing-Enabled Smart Cities: A Comprehensive Survey [article]

Latif U. Khan, Ibrar Yaqoob, Nguyen H. Tran, S. M. Ahsan Kazmi, Tri Nguyen Dang, Choong Seon Hong
2020 arXiv   pre-print
In this survey, we highlight the role of edge computing in realizing the vision of smart cities. First, we analyze the evolution of edge computing paradigms.  ...  Recent years have disclosed a remarkable proliferation of compute-intensive applications in smart cities.  ...  guidelines Data sparsity due to mobility • High back-haul congestion • High latency in content delivery • Deep learning assisted cache content prediction • Reinforcement learning based mobility-aware  ... 
arXiv:1909.08747v2 fatcat:nwnyec5gnfdmtd3msohsbkgulm

Applications of Deep Reinforcement Learning in Communications and Networking: A Survey [article]

Nguyen Cong Luong, Dinh Thai Hoang, Shimin Gong, Dusit Niyato, Ping Wang, Ying-Chang Liang, Dong In Kim
2018 arXiv   pre-print
In such networks, network entities need to make decisions locally to maximize the network performance under uncertainty of network environment.  ...  This paper presents a comprehensive literature review on applications of deep reinforcement learning in communications and networking.  ...  CNNs are employed in the DQL to predict a continuous value of the mobile user's remaining data.  ... 
arXiv:1810.07862v1 fatcat:qc3mqk2norazvc2xnynau6bqzu

A Cross-Layer Path Selection Scheme for Video Streaming over Vehicular Ad-Hoc Networks

Mahdi Asefi, Jon W. Mark, Xuemin Shen
2010 2010 IEEE 72nd Vehicular Technology Conference - Fall  
not shared so deeply by other types of existing networks, particularly, in terms of mobility of nodes, and end-to-end quality of service (QoS) provision.  ...  The emerging vehicular ad-hoc networks (VANETs) offer a variety of applications and new potential markets related to safety, convenience and entertainment, however, they suffer from a number of challenges  ...  Mobile IP Management at Transport Layer Basic extension of Mobile IPv6 for NEMO is used in vehicular networks.  ... 
doi:10.1109/vetecf.2010.5594547 dblp:conf/vtc/AsefiMS10 fatcat:txqymchwxvd7tnvl6qlp5wqavi

Applications of Deep Reinforcement Learning in Communications and Networking: A Survey

Nguyen Cong Luong, Dinh Thai Hoang, Shimin Gong, Dusit Niyato, Ping Wang, Ying-Chang Liang, Dong In Kim
2019 IEEE Communications Surveys and Tutorials  
In such networks, network entities need to make decisions locally to maximize the network performance under uncertainty of network environment.  ...  This paper presents a comprehensive literature review on applications of deep reinforcement learning in communications and networking.  ...  ., UAV and vehicular networks. In this section, we review the other uses of DRL in communications and networking.  ... 
doi:10.1109/comst.2019.2916583 fatcat:5owsswhhrbctnirdtxre6mhv24

Social Sensing [chapter]

Charu C. Aggarwal, Tarek Abdelzaher
2012 Managing and Mining Sensor Data  
Some examples of such applications include GPS applications on mobile devices, accelerometers, or location sensors designed to track human and vehicular traffic.  ...  In this chapter, we provide a broad survey of the work in this important and rapidly emerging field.  ...  The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory  ... 
doi:10.1007/978-1-4614-6309-2_9 fatcat:7k74wrhmozearbfbfod3yqjxcm

A Survey of Anticipatory Mobile Networking: Context-Based Classification, Prediction Methodologies, and Optimization Techniques [article]

Nicola Bui, Matteo Cesana, S. Amir Hosseini, Qi Liao, Ilaria Malanchini, Joerg Widmer
2017 arXiv   pre-print
In particular, we identify the main prediction and optimization tools adopted in this body of work and link them with objectives and constraints of the typical applications and scenarios.  ...  This paradigm made modern solutions, such as recommendation systems, a ubiquitous presence in today's digital transactions.  ...  Finally, inter-download time can be modeled [102] and subsequently predicted for quality optimization. The work in [103] targets energy-efficient resource scheduling in mobile radio networks.  ... 
arXiv:1606.00191v3 fatcat:me4ufu7gsjcmtcrs3m6g4jf2am
« Previous Showing results 1 — 15 out of 270 results